1. Field of the Invention
The present invention relates to a half-tone image processing technique, and more particularly, to a tone dependent green-noise error diffusion method capable of enhancing printing quality and printing apparatus thereof.
2. Description of the Prior Art
Half-tone image processing technique is extensively applied to printing apparatuses. Half-tone image processing technique transfers a continuous-tone image into a two-level half-tone image, and a printing apparatus selectively performs a printing operation according to pixels of the two-level image, thereby generating a printed result close to a continuous-tone image. Frequency modulation half-tone image processing method, e.g., an error diffusion method, is frequently used on inkjet printers. However, a laser printer that employs this method will suffer color shift. To prevent this color shift problem, laser printers usually employ an amplitude modulation half-tone image processing method. Nevertheless, the printer employing this method usually suffers from a moire pattern when performing a copying operation.
The green-noise error diffusion method, which acquires a characteristic between the frequency modulation half-tone image processing method and the amplitude modulation half-tone image processing method, is capable of solving the phenomenon of color shift for laser printers as well as the moire pattern generated when performing copying operations. Please refer to FIG. 1 and FIG. 2. FIG. 1 and FIG. 2 are diagrams of an operation of a conventional green-noise error diffusion method. FIG. 1 (including sub-diagrams FIG. 1A, FIG. 1B, FIG. 1C and FIG. 1D) indicates pixel color level values modified by an output feedback apparatus, and FIG. 2 (including sub-diagrams FIG. 2A, FIG. 2B, FIG. 2C and FIG. 2D) indicates pixel color level values diffused by an error diffusion apparatus. As shown in FIG. 1A, (x, y) indicates a pixel which is currently being processed, wherein the color level value thereof is 155; (x−1, y−1), (x, y−1), (x+1, y−1), (x−1, y) are pixels which are already processed; and (x+1, y), (x−1, y+1), (x, y+1), (x+1, y+1) are pixels which are not processed yet. FIG. 1B is a diagram of a distribution of output feedback weighting values: the mark * indicates the pixel (x, y) which is currently processed, the value 0.8 indicates a second output feedback weighting value of the pixel (x, y), and the value 1.2 indicates a first output feedback weighting value of the pixel (x, y). FIG. 1C indicates output feedback values of neighboring pixels (x−1, y) and (x, y−1) of the pixel (x, y) in FIG. 1A that are derived according to the output feedback weighting values in FIG. 1B. FIG. 1D indicates a modified color level value derived from the pixel (x, y) in FIG. 1A plus the output feedback values in FIG. 1C.
Please refer to FIG. 2. Since the modified color level value 359 of the pixel (x, y) in FIG. 1D is larger than a threshold 127, a two-level value of the pixel (x, y) is set as 255, as shown in FIG. 2A. FIG. 2B is a diagram of a distribution of error diffusion weighting values, where the mark * indicates the pixel (x, y) which is currently processed, and the two values 0.5 and 0.5 indicate a first error diffusion weighting value and a second error diffusion weighting value of the pixel (x, y), respectively. The error value between the color level value 155 of the pixel (x, y) in FIG. 1A and the two-level value 255 of the pixel (x, y) in FIG. 2A is (−100). FIG. 2C indicates error diffusion values derived from a calculation of the error value (−100) according to the error diffusion weighting values in FIG. 2B. Finally, the error diffusion values in FIG. 2C are diffused to neighboring pixels (x+1, y) and (x, y+1) of the pixel (x, y) in FIG. 2A to thereby derive diffused pixel color level values as shown in FIG. 2D. The respective flows in FIG. 1 and FIG. 2 are repeated until all the pixels are processed.
The green-noise error diffusion method still suffers from image defects of a regular pattern in bright color level, middle color level and dark color level; therefore, there still remains room for improvement of this prior art method.